Technical session talks from ICRA 2012

TechTalks from event: Technical session talks from ICRA 2012

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Control of UAVs

Standard quadrotor UAVs possess a limited mobility because of their inherent underactuation, i.e., availability of 4 independent control inputs (the 4 propeller spinning velocities) vs. the 6 dofs parameterizing the quadrotor position/orientation in space. As a consequence, the quadrotor pose cannot track an arbitrary trajectory over time (e.g., it can hover on the spot only when horizontal). In this paper, we propose a novel actuation concept in which the quadrotor propellers are allowed to tilt about their axes w.r.t. the main quadrotor body. This introduces an additional set of 4 control inputs which provides full actuation to the quadrotor position/orientation. After deriving the dynamical model of the proposed quadrotor, we formally discuss its controllability properties and propose a nonlinear trajectory tracking controller based on dynamic feedback linearization techniques. The soundness of our approach is validated by means of simulation results.

In this paper, we present haptic teleoperation of underactuated unmanned aerial vehicles by providing a multidimensional generalization of the virtual slave concept. The proposed control architecture is composed of high-level and low-level controllers. The high-level controller commands the vehicle to accomplish specific tasks and renders both the state and the environment of the vehicle to the operator through haptic feedback. The low-level controller interprets the command signals from the operator, regulates the dynamics of the vehicle and feeds back its state to the high-level loop. Passivity of the teleoperation loop is always ensured independently of the choice of implementation of the low-level controller and the configuration of the flying hardware by a passivity-enforcing supervisor, which associates every action of the slave with an energy expense that can only be made available from a multi-state energy tank. The effectiveness of the proposed algorithm is illustrated with simulations and experimental tests.

Research on insect-inspired flapping-wing micro-aerial vehicles (FWMAV) has grown steadily in the past decade, aiming to address unique challenges in morphological construction, force production, and control strategy. In particular, effective methods for motion control still remain an open problem. This paper analyzes the mechanical impedance properties of the joint and their role in rotation of the wing and force production. The results suggest that in addition to previously observed relationship between set point and drag [1], the average lift force is also related to the stiffness of the joint. Furthermore, as long as changes in impedance properties are small, net lift and drag production are almost independent. These relationships are the basis of â€˜tunable impedanceâ€™ technique, a new approach to force/motion control in FWMAVs. A simple controller designed based on this method is used to simulate various flight maneuvers. The simulated MAV demonstrates exceptional performance, even in presence of measurement noise. This technique requires a fixed stroke profile for both wings, thus allowing to use a single stroke actuator â€“ in a real MAV â€“ with a bandwidth as low as the frequency of flapping. Impedance actuators also prove to have low bandwidth requirements.

Indoor aerial robots are useful in many applications due to their size, agility and ability to hover. However, tweaking a state-feedback controller to fly stably takes either intensive human supervision, or extensive modeling and identification, hence has never been trivial. In this paper, we give a successful flight controller design that can learn from a single demonstration performed by human and hover indoor aerial robots autonomously on maiden flight.

The goal of this research is to develop a lightweight, high bandwidth control actuator that can be integrated on a flapping wing nano air vehicle (NAV). Traditional control actuators for air vehicles including DC servomotors and shape memory alloy are either too heavy or too slow to control a fast moving NAV. This paper develops a new bio-inspired active tail mechanism to stabilize an inverted pendulum with the same mass and inertia as the NAV. An analysis of the dynamic model shows a critical angle at which the control actuator can no longer stabilize the pendulum varies significantly with link lengths and mass ratios. Based on this dynamic model, an LQR controller is developed and implemented as a state space controller on a microcontroller based test setup. Using a gyroscope to measure the pendulumâ€™s angular velocity and estimate the angle, the active tail mechanism was able to stabilize the pendulum for over five minutes before falling due to drift in the gyroscope sensor.

Swarms of flying robots are promising in many applications due to rapid terrain coverage. However, there are numerous challenges in realising autonomous operation in unknown indoor environments. A new autonomous flight methodology is presented using relative positioning sensors in reference to nearby static robots. The entirely decentralised approach relies solely on local sensing without requiring absolute positioning, environment maps, powerful computation or long-range communication. The swarm deploys as a robotic network facilitating navigation and goal directed flight. Initial validation tests with quadrotors demonstrated autonomous flight within a confined indoor environment, indicating that they could traverse a large network of static robots across expansive environments.